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Industrial IoT in the advancement of organizations consigns to the next level in order to trace and manage every single activity of their entities. However, the interdependence, implementation and communication among such wireless devices also known as IoT devices that lead to various secrecy and personnel concerns. Even though the use of smart sensors in industries assists and reduces human efforts with the increased quality besides of enhanced production cost. Several attacks may further encountered by various attackers by hacking several sensors/objects/devices activities. In this paper, in order to preserve transparency and secure each and every activity of smart sensors, we have proposed a secure wireless mechanism using Blockchain technology that stores extorted proceedings of each record into number of blocks. Further, the simulation results of proposed blockchain mechanism are executed against various security transmission processes. In addition, the simulated results are scrutinized besides traditional mechanism and verified over certain metrics such as Probability of attack success, ease of attack detection by the system, falsification attack, authentication delay and probabilistic scenarios to appraise the authenticity of IoT devices.

This paper proposes a circularly polarized 2 × 2 antenna array for C-band wireless applications. The most attractive feature of the proposed design is that it is only fabricated on a single layer of a dielectric substrate, while maintaining wideband operation and high gain radiation as well. The single-layer design is able to significant reduce the antenna’s complexity. The array element is based on a truncated corner patch and a periodic structure. The final prototype of 2 × 2 antenna array with overall dimensions of 1.2λ × 1.2λ × 0.04λ, where λ is the lowest operating frequency, was fabricated and experimentally validated. The proposed array yields a measured impedance bandwidth of 42.9% (4.4–6.8 GHz) and a measured 3-dB axial ratio bandwidth of 36.4% (4.5–6.5 GHz). Within the operating band, good radiation patterns are achieved and the boresight gain is from 9.5 to 11.5 dBic. Compared with the other reported single-layer sequential-fed antenna arrays in literature, the proposed shows the best operating bandwidth with competitive gain radiation.

Inter satellite optical wireless communication (IsOWC) is an emerging transmission technology which is capable of transporting high-speed data between two satellites estranged in outer space and revolving in the same or different orbits. IsOWC links have been considered very crucial for the purpose of providing global coverage for information transmission throughout the world. This work reports the modeling and performance investigation of a novel hybrid wavelength division multiplexing–polarization division multiplexing based IsOWC transmission system incorporating an orthogonal modulation scheme combining carrier suppressed return to zero–differential quadrature phase shift keying–polarization shift keying formats to transmit three independent 40 Gbps data streams simultaneously at different signal parameters. The results show a successful transmission of 3.84 Tbps information over 58,000 km link range with acceptable Q Factor (> 6 dB) and BER (≤ 10−9) using the proposed system. The performance comparison of the proposed system with existing work has also been discussed in this paper.

The core objective behind this research paper is to implement a hybrid optimization technique along with proactive routing algorithm to enhance the network lifetime of wireless sensor networks (WSN). The combination of two soft computing techniques viz. genetic algorithm (GA) and bacteria foraging optimization (BFO) techniques are applied individually on destination sequence distance vector (DSDV) routing protocol and after that the hybridization of GA and BFO is applied on the same routing protocol. The various simulation parameters used in the research are: throughput, end to end delay, congestion, packet delivery ratio, bit error rate and routing overhead. The bits are processed at a data rate of 512 bytes/s. The packet size for data transmission is 100 bytes. The data transmission time taken by the packets is 200 s i.e. the simulation time for each simulation scenario. Network is composed of 60 nodes. Simulation results clearly demonstrates that the hybrid approach along with DSDV outperforms over ordinary DSDV routing protocol and it is best suitable under smaller size of WSN.

In this paper, we propose a data aggregation back pressure routing (DABPR) scheme, which aims to simultaneously aggregate overlapping routes for efficient data transmission and prolong the lifetime of the network. The DABPR routing algorithm is structured into five phases in which event data is sent from the event areas to the sink nodes. These include cluster-head selection, maximization of event detection reliability, data aggregation, scheduling, and route selection with multi attributes decision making metrics phases. The scheme performs data aggregation on redundant data at relay nodes in order to decrease both the size and rate of message exchanges to minimize communication overhead and energy consumption. The proposed scheme is assessed in terms of packet delivery, network lifetime, ratio, energy consumption, and throughput, and compared with two other well-known protocols, namely “information-fusion-based role assignment (InFRA)” and “data routing for in-network aggregation (DRINA)”, which intrinsically are cluster and tree-based routing schemes designed to improve data aggregation efficiency by maximizing the overlapping routes. Meticulous analysis of the simulated data showed that DABPR achieved overall superior proficiency and more reliable performance in all the evaluated performance metrics, above the others. The proposed DABPR routing scheme outperformed its counterparts in the average energy consumption metric by 64.78% and 51.41%, packet delivery ratio by 28.76% and 16.89% and network lifetime by 42.72% and 20.76% compared with InFRA and DRINA, respectively.

Route failures pursued by rerouting is common in WSNs due to the unpredictable network dynamics and autonomous node behaviors. Optimal selection of neighbor is henceforth necessary to ensure profitable packet delivery and application support. In this manuscript, we propose a Weighted Path Rediscovery (WPR) routing for improving the routing decisions of WSN nodes. This routing algorithm is intended to prevent backtracking and curtail looped routing in WSNs. WPR precis’s conventional routing based on link expiration time (let) and fun factor at the time of neighbor discovery and reinforced routing, respectively. The two distinct features are converged using link stability factor to ensure the improved routing satisfying node’s behavior constraints. This improves the quality of packet transmission and minimizes routing complexity. The proposed routing algorithm is assessed using the factors: Packet Delivery Ratio (PDR), End-to-End Delay, Overhead and Connection Ratio.

This research analyzes how to exploit the BDA (Big Data Analytics) to help the conversion of a city into a smarter location. We execute an in-depth test case of a transforming city and take the prospect of methods enabling to reveal the diverse opportunities that BDA has created to promote the achievement of tourism destinations. Our study reveals 3 kinds of types of BDA concepts and shows how well these contexts are cascading updated to enable informed intelligent tourism choices as well as development sustainability.

Nature has made a huge impact on human’s diurnal lives in finding solutions for complex problems. Majority of the people are receiving benefits by the advanced technologies. Without the aid of computers, it is hard to imitate the problem solving techniques being implemented by nature. Bio-mimicry is one such study which enables the researchers in solving human problems by emulating and mimicking nature. This emerging technology fetches its sources from bio-inspired engineering at various levels. BIC, short for bio-inspired computing or biologically inspired computation, found to be a broad term, which comprises different fields like computer science, mathematics and biology. Mix and match of various biological and computational processes is the reliable means for researchers in this regard and this leads to the convergence of two fields: computer science and biology. In recent past, the bio-inspired optimization algorithms are highly convincing to bring out best expositions for intricate snags by joining hands with machine learning. Along with BIC, swarm intelligence (SI) is also equally gaining importance. Bio-inspiring algorithms like ant colony algorithm, bat algorithm, cuckoo search, fire-fly algorithms, and particle swarm optimization possess extensive applications in almost all fields of science and engineering. Swarm intelligence is the collective behavior of decentralized, self-organized systems, though they are natural or artificial and it is based on meta-heuristic approach which generally pulls out an approximate optimal solution independent of the problems in less time. Nowadays, the information technology advancements induce felons to commit copious cybercrimes using cyberspace. More sophisticated cyber-defense systems are to be devised essentially, since (1) cyber-infrastructures are extremely open and prone to infringements and other intimidations and (2) human intervention and physical devices are not adequate to monitor and fortify the cyber-infrastructures. The ability to detect a wide variety of threats and adaptability to make quick real-time decisions, flexibility and robustness are the major expected qualities for these systems. Abundant BIC approaches incorporated with artificial intelligence (AI) using IOT plays a vital role in cybercrime detection and prevention. Let us have a cattle graze of few techniques of AI associated with bio-inspired computing and its futuristic scope over human community to combat cybercrimes and this review would pave the alleyway for forthcoming studies to cherry-pick algorithms based on fitment.

A wireless system model which typically consists of a beginning node, multiple relays, and an ending node, has been considered. The conventional selection combining schemes are not suitable for cooperative diversity systems due to its inherent detection errors. The relays forward beginning nodes information through a decode and forward protocol. The detection errors can be minimized by having a threshold at the relay. The relays participate in the cooperation process only if the instantaneous signal-to-noise ratio (SNR) of the beginning node to relay node is more than a fixed threshold. We derive the end-to-end symbol error probability of this scheme for M-ary phase-shift keying using paired error method for relay networks in the presence of flat Rayleigh fading. We numerically find the optimum value of relay-threshold. Numerical results show that the relay-threshold selection combining outperforms the conventional selection combining in terms of SNR gain.

In order to elevate the utility of licensed spectrum bands credit to coexistence within the same network of licensed or primary users and cognitive or secondary users, it is intended to have cognitive radio $(CR)theo/y$. Effective resource allocation between secondary and primary users is the most significant key aspect in this environment. In Cognitive Radio Networks (CRNs), resource allocation is used for total utilization of frequency spectrum Limitations such as transmission power, interference threshold of primary users and traffic demands of secondary users builds the challenge for maximizing the energy-efficiency. In order to overcome the problem of maximum energy consumption and minimum energy efficiency, a Hybrid Water Filling (HWF) Algorithm is proposed. Combination of Multi-Objective Particle Swarm optimization (MOPSO) and Iterative Water Filling (IWF) algorithm is baptized as HWF. MOPSO is used to optimize the sub channels and energy allocation to achieve the highest capacity under the total energy constraint. Thus by combining IWF with MOPSO, the energy efficiency is augmented and provides optimal energy transmission for resource allocation. The simulation results illustrate that the proposed algorithm could achieve the optimal energy allocation than the existing one in less amount of time.

Radio-over-Free-Space Optics (RoFSO) is a key technology for providing high-speed communication links in rural areas. In this work, an orthogonal frequency division multiplexing based RoFSO transmission link has been designed by adopting hybrid wavelength division multiplexing (WDM), mode division multiplexing (MDM) and multibeam technique. The proposed link is investigated under heavy fog weather conditions and its performance is compared for 1-beam and 4-beams transmission using numerical simulations. The numerical results show faithful transportation of high-speed data at 2000 m with acceptable performance of the link. Furthermore, the link performance is compared with previously reported works and the proposed RoFSO link with hybrid WDM-MDM-multibeam technique demonstrates an enhanced link range and transmission capacity performance.

This research concept deals with Parallelizes PSO-SA model which combines the particle swarm optimization (PSO) and Simulated Annealing (SA). Parallel PSO-SA operates by parallelizing the operation of each of the particles and Multistart PSO runs parallel several normal versions of PSO embedded with Simulated Annealing in parallel. The experimental results were conducted on benchmark data sets and the proposed approach can reduce the time complexity and also to increase classification accuracy.

Artifacts, over-enhancement and unnatural effects are rarely produced by current dark image boosting algorithm. These problems are solved by content – aware algorithm which boost dark images, sharpens edges, exposes textured details and conserves flat region smoothness and also gives ad-hoc transformation for each image. We analyze the image contrast of boundary and textured regions, and group the information of common characteristics from extracted transformation functions. The outputs are adaptively mixed by Human Vision System (HVS) characteristics, to boost the Image details. Results proves that the algorithm can automatically process a shadow and dark areas, indoor and outdoor lighting and face images.